Dynamic client interaction for search

ABSTRACT

A system for guiding a search for information is presented. The system comprises a user interface that accepts a phrase and receives at least one suggestion based at least in part on the phrase. The system also includes a phrase suggestion engine that matches the phrase with the at least one suggestion. Methods of using the system are also provided.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims benefit under 35 U.S.C. §119(e) from U.S.Provisional Patent Application Ser. No. 60/655,583, entitled “DYNAMICCLIENT INTERACTION FOR SEARCH” and filed on Feb. 23, 2005. The entiretyof the aforementioned application is hereby incorporated by reference.

BACKGROUND

The amount of data available to information seekers has grownastronomically, whether as the result of the proliferation ofinformation sources on the Internet, or as a result of private effortsto organize business information within a company, or any of a varietyof other causes. As the amount of available data grows, so does the needto be able to search through that information to locate specific items.A related problem is the need for users to properly construct queries inorder to locate desired information.

Search systems include such systems as web search engines and databaseinterfaces, among others. When a user performs a search for information,that user typically must create and construct a query that the userbelieves will produce desired results. The creation of such a query isprone to events that can negatively impact the accuracy of searchresults, such as spelling errors and lack of knowledge of relevantsearch terms. In many systems, queries may also tend towards longstrings that can be unwieldy to enter. These and other factors canincrease the time and effort needed to locate desired information.

User interfaces for search functions also impact both the ease ofperforming a search and the accuracy of search results. A typicalinteraction today involves a user typing some keywords to enter as aquery, performing a search based on those keywords, and viewing theresults. The user must predict what is a necessary or sufficient queryto obtain desired results. Inaccurate predictions result in undesiredresults. Queries that are too short may inadequately refine the resultset. Queries that are too long may inadvertently exclude desirableresults. Queries that use an unfortunate choice of terms or operatorsmay inadequately refine the results or exclude desirable results. A usermay have to perform many iterations of this process until desiredresults are obtained. Therefore, there is a need for systems and methodsthat can minimize query errors and assist in query creation to performeffective searches.

SUMMARY

The following presents a simplified summary in order to provide a basicunderstanding. This summary is not an extensive overview. It is neitherintended to identify key or critical elements nor to delineate scope.Its sole purpose is to present some concepts in a simplified form as aprelude to a more detailed description that is presented later.Additionally, section headings used herein are provided merely forconvenience and should not be taken as limiting in any way.

A user interface is provided that interacts with a user to assist theuser during the creation of a search query. This assistance can guidethe user during the creation of the query to develop a query that islikely to obtain search results desired by the user. Additionally, theguidance can assist the user by suggesting likely terms that can be usedin a search query. Specific instances of assistance or guidance duringcreation of the query can dynamically change in response to useradditions to, or refinements of, the query.

A search system includes a dynamic user interface that guides a userthrough the creation of a search query. As the query is constructed bythe user, the search system provides preliminary results to the user.The user can then terminate the construction of the query and selectfrom among the preliminary results presented. Additionally oralternatively, the user can continue to refine the search query andobtain new or updated search results dynamically as such refinementoccurs or within a short duration of time thereafter.

A method of searching is provided. The method includes dynamicallysuggesting to a user at least one search query that the user may selectas the user constructs the search query. The user can add, delete, orchange search terms to focus the query to obtain desired results. Apreview of results that can be obtained with a current or suggestedquery allows the user to determine whether the query being constructedwill serve the needs of the user.

The disclosed and described components and methods comprise the featureshereinafter fully described and particularly pointed out in the claims.The following description and the annexed drawings set forth in detailcertain illustrative aspects. These aspects are indicative, however, ofbut a few of the various ways in which the disclosed components andmethods can be employed. Specific implementations of the disclosed anddescribed components and methods can include some, many, or all of suchaspects and their equivalents. Variations of the specificimplementations and examples presented herein will become apparent fromthe following detailed description when considered in conjunction withthe drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system block diagram of a dynamic search system.

FIG. 2 is a system block diagram of a dynamic search client.

FIG. 3 is a system block diagram of a guide engine and user interfacesystem.

FIG. 4 is a system block diagram of a dynamic search user interface.

FIG. 5 is system block diagram of a dynamic search client that alsoincludes user feedback functions.

FIG. 6 is a system block diagram of a dynamic search client that alsoincludes content association functions.

FIG. 7 is a system block diagram of a dynamic search client system thatincludes structuring functions.

FIG. 8 is a diagram of a user interface.

FIG. 9 is a flow diagram showing processing of a method that can be usedin conjunction with components disclosed or described herein.

FIG. 10 is a flow diagram showing processing of a method that can beused in conjunction with components disclosed or described herein.

FIG. 11 is a flow diagram showing processing of a method that can beused in conjunction with components disclosed or described herein.

FIG. 12 is a flow diagram showing processing of a method that can beused in conjunction with components disclosed or described herein.

FIG. 13 is a flow diagram showing processing of a method that can beused in conjunction with components disclosed or described herein.

FIG. 14 is a flow diagram showing processing of a method that can beused in conjunction with components disclosed or described herein.

FIG. 15 is a schematic block diagram of a sample-computing environment.

FIG. 16 is a schematic block diagram of an exemplary computer.

DETAILED DESCRIPTION

As used in this application, the terms “component,” “system,” “module,”and the like are intended to refer to a computer-related entity, such ashardware, software (for instance, in execution), and/or firmware. Forexample, a component can be a process running on a processor, aprocessor, an object, an executable, a program, and/or a computer. Also,both an application running on a server and the server can becomponents. One or more components can reside within a process and acomponent can be localized on one computer and/or distributed betweentwo or more computers.

Disclosed components and methods are described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the disclosed subject matter. It may beevident, however, that certain of these specific details can be omittedor combined with others in a specific implementation. In otherinstances, certain structures and devices are shown in block diagramform in order to facilitate description.

Additionally, although specific examples set forth may use terminologythat is consistent with client/server architectures or may even beexamples of client/server implementations, skilled artisans willappreciate that the roles of client and server may be reversed, that thedisclosed and described components and methods are not limited toclient/server architectures and may be readily adapted for use in otherarchitectures, specifically including peer-to-peer (P2P) architectures,without departing from the spirit or scope of the disclosed anddescribed components and methods. Further, it should be noted thatalthough specific examples presented herein include or referencespecific components, an implementation of the components and methodsdisclosed and described herein is not necessarily limited to thosespecific components and can be employed in other contexts as well.

FIG. 1 is a system block diagram of a dynamic search system 100. Thedynamic search system 100 includes a user interface 110 that providesaccess to the system for a human user. The user interface 110 can beimplemented as a command-line interface (“CLI”), a graphical userinterface (“GUI”), a text-based interface, or may combine aspects of anyof the foregoing interfaces in addition to other appropriate aspects.For example, a GUI may include aspects or elements such as graphicalon-screen buttons, menus, including drop-down menus, text boxes, radiobuttons, check boxes, or other appropriate elements. Use of suchelements allows for an implementer of the disclosed system to chooseelements that are appropriate for a specific implementation. Preferably,the user interface 110 is interactive and provides responsiveinformation to the user as the user types.

The dynamic search system 100 also includes a search server 120. Thesearch server 120 can perform phrase suggestion tasks and search tasks.In this example, as well as others, a phrase can include any datum thatcan be entered by a user and specifically includes complete words,groups of words, characters (including a single character or symbol),wildcard characters or symbols, prefixes, infixes, suffixes, and thelike. When a component such as the search server 120 performs asuggestion task or provides a suggestion, the suggestion can includephrase completions, spelling corrections, additions to prefixes,infixes, or suffixes, substitutions for wildcard characters whether ornot such substitutions include the same or a similar number ofcharacters as those wildcard characters included in an original phrase,or even wholesale substitutions of phrases.

It should be understood that a type of data that can be used as a phrasecan vary according to specific features of the user interface that isprovided. For example, if the user interface is responsive to speechinput, the phrase can include audio input of words, letters, or othertypes of phrases such as those disclosed and described above. If theuser interface is responsive to handwritten input, the phrase caninclude any datum that can be recognized by that user interface andspecifically can include any symbol that can be input.

The search server 120 includes both a guide engine 130 and a searchengine 140. The guide engine 130 communicates with the user interface110 to accept information from and transmit information to the userinterface 110. The search engine 140 also communicates with the userinterface 110 to accept information from the user interface 110 andtransmit information back. The information transmitted from the searchengine 140 to the user interface 110 is typically in the form of searchresults.

In accordance with this specific example, the information transmittedfrom the user interface 110 to the guide engine 130 is in the form ofone or more phrases. One example of a phrase is a single character thatis typed on a keyboard by the user. Alternatively, a phrase including agroup of typed characters can be sent. The guide engine 130 can then usethe phrase as a basis to generate suggestions. Specifically, the phrasecan be used as a prefix for suggestions that begin with the phrase, as asuffix for suggestions that end with the phrase, as a root in the sensethat suggestions can contain some form of the phrase, or simply as abasis upon which suggestions with related terms may be provided.

FIG. 2 is a system block diagram of a dynamic search client 200. Thedynamic search client 200 includes a user interface 210. The userinterface 210 can be a command-line interface, a graphical userinterface, a text-based interface, or another type of interface that mayor may not include one or more features of these types of interfaces. Aspecific example of a suitable interface is an interface that is basedupon a web browser. Another possible interface is a Braille interfacethat conveys information that the user can receive through touching theinterface. As previously described in conjunction with FIG. 1, the userinterface 210 can be adapted in a wide variety of ways specific to adesired implementation.

As will be appreciated from this disclosure and detailed description,various implementations of the components and methods disclosed anddescribed herein can be constructed or performed on a wide variety ofgeneral-purpose computing devices, such as the computer of FIG. 16.Additionally or alternatively, other computing devices, including butnot limited to special-purpose computing devices such as data entryterminals, among others, and mobile computing devices, such as wirelesstelephones, mobile computers, personal digital assistants (PDAs),personal information managers (PIMs), and the like, can also be used asplatforms upon which a specific implementation can be built or used.

The disclosed and described components and methods can be of particularuse in conjunction with mobile devices or other devices or scenarioswhen a user is unable to quickly enter data, such as when a user isentering text on a cellular telephone number pad or on an abbreviatedkeyboard, or using a stylus to select letters presented on a displayscreen, among others. Further, disclosed and described components andmethods can be useful in noisy data entry environments such as whenentering data by handwriting using a stylus or specially adapted peninput device such as a pen that tracks its position as it is movedacross a surface having a specially designed surface pattern or someother mechanism to track position of the pen, or when using a speechrecognition system, among others. In these and other environments, thedisclosed and described components and methods can be used to assistdata entry tasks and potentially overcome data entry errors, forexample, in the misrecognition of a spoken word entry, among others, bysuggesting phrases.

The dynamic search client 200 also includes a phrase suggestion engine220. In this context, and in other places herein where required orappropriate and as described above, a phrase can include not only aplurality of words but also a single word, a portion or portions of oneor more words, and even a single character, among other things. Thephrase suggestion engine 220 can interact with the user interface 210 inorder to assist in suggesting phrases to substitute for that which auser is entering.

With reference to phrase suggestion tasks, the phrase suggestion engine220 can suggest a phrase to substitute in place of the phrase that isbeing entered or has been entered by the user. For example, if a userenters “aut,” the phrase suggestion engine 220 can suggest the term“automobile.” Similarly, in a speech-based interface, if a user says“auto,” the phrase suggestion engine 220 can suggest “automobile.” Inanother example, if a user enters the term “cars,” the phrase suggestionengine 220 can suggest “sports cars dealers in Seattle, Wash.”

Additionally or alternatively, the phrase suggestion engine 220 cansuggest a query based upon a pattern that can include wildcards. Forinstance, if the user enters a phrase such as “Leo* DaVinci” the phrasesuggestion engine 220 can suggest “Leonardo DaVinci.” If a user speaks“DaVinci” but a voice recognition component identifies the input as“Davis,” the phrase suggestion engine 220 can suggest queries thatinclude sound-alike phrases such as “DaVinci.” Other forms or types ofsuggestions are possible and will become apparent to those of ordinaryskill in the art upon reading this disclosure. Such other forms or typesinclude, but are not limited to, spelling correction, noisy inputcorrection, and grammar correction.

To perform such suggestion tasks, the phrase suggestion engine 220 canaccess a phrase data store 230. The phrase data store 230 can be asimple list of common search terms, dictionary words, or phrases, can besuch a list combined with probabilistic or other weighted measures, orcan be another suitable set of phrases that can be used to suggest asubstitute for a phrase entered by a user at the user interface 210. Thephrase suggestion engine 220 can use a portion of a phrase entered by auser at the user interface 210 as a root or some other basis to suggest,predict, infer, or otherwise determine a likely phrase that the user isentering.

A search engine 240 can also interact with the user interface 210 of thedynamic search client 200. The search engine 240 can be located on aremote server, such as in the case of many of the search engines used tofind content on the World Wide Web. The search engine 240 can also be acomponent that is located on a local machine, such as with a desktopsearch component. A search data store 250 can contain information thatcan be accessed and searched by the search engine 240. The search datastore 250 can be a file, a group of files, a database, or any otherappropriate data store that can contain information to be searched.

An example of the functioning the dynamic search client 200 follows. Inoperation, a user can enter a phrase at the user interface 210. Suchentry can be by typing, speaking, gesturing, or any other data entrymethod that can be employed with the user interface 210. As each portionof the phrase is entered by the user, the user interface 210 sends suchportion (or alternatively, an aggregated portion including portionsalready entered) to the phrase suggestion engine 220. The phrasesuggestion engine 220 uses the phrase as a root or other basis todetermine an appropriate phrase to suggest as a replacement orsubstitute for the entered phrase. This determination can be predictivebased upon available dictionary words, past searches by the user orother users, or some other available means. The phrase suggestion engine220 obtains appropriate phrases from the phrase data store 230. Thisprocedure of obtaining a phrase to use as a root or other basis frominformation entered into the user interface 210 and suggesting a phrasebased upon information from the phrase data store 230 can beincrementally repeated as phrases are constructed or completed and a newentry of a datum or data is begun by the user.

Upon completion of a query that includes one or more suggested phrases,the user interface 210 sends the query to the search engine 240. Thesearch engine 240 uses the query to find information in the search datastore 250 that is responsive to the query. Once such responsiveinformation is found, or alternatively a failure to find responsiveinformation is determined, the search engine 240 sends the responsiveinformation or a failure message to the user interface 210. The userinterface 210 then presents the response of an affirmation or failuremessage to the user. It should be noted that such searches performed bythe search engine can also be performed incrementally as each individualphrase is suggested by the phrase suggestion engine 220. The userinterface 210 can then provide dynamically updated search results basedupon a continuously-evolving search query that is based at least in partupon suggestions. In at least this case, the search engine 240 can useprevious result sets or perform additional computational or search taskson the query to improve search performance as the user enters additionaldata.

FIG. 3 is a system block diagram of a guide engine and user interfacesystem 300. A user interface 305 can transmit information to a guideengine 310. A query segment engine 320 can accept information from theuser interface 305, such as a phrase, and create a query segment fromthat information. The created query segment is then sent to a matchingengine 330. The matching engine 330 accesses information from a querysuggestion data store 340 to match a query segment with a suggestion. Anumber of methods may be employed to perform the matching, including,but not limited to, a simple lookup of words that begin with a singlecharacter in an entered phrase, a probability-based suggestion usingpopular phrases from a group of users, or a customized suggestion basedupon preferences and likely search topics from a specific user.

The query suggestion data store 340 can be implemented in a variety ofways. For example, the query suggestion data store 340 can be a flatdictionary file containing common search terms to be used assuggestions. Such a file may be combined with a probabilistic ranking sothat terms appear in order of likelihood for search rather thanalphabetically or using some other ordering method. The query suggestiondata store 340 can also be implemented as a table or tables in adatabase, again, with or without probability information. Otherappropriate data structures can be employed, depending upon the needs ordesires of a specific implementer.

One example of a possible mode of operation of the guide engine and userinterface system 300 follows. In operation, the user interface 305accepts an entered phrase from a user. As the user types the phrase at akeyboard, portions of the phrase, such as single characters or groups ofcharacters, are transmitted to the query segment engine 320 of the guideengine 310. The query segment engine 320 assembles the portions of thephrase it has received into a query segment. This query segment is usedby the matching engine 330 as a basis for finding suggestions in thequery suggestion data store 340. The query segment may be used as aprefix, a root, a suffix, or a basis for other, typically similar orrelated, terms. The matching engine selects one or more suggestions andtransmits those suggestions to the user interface 305.

FIG. 4 is a system block diagram of a dynamic search user interface 400.A user interface 410 includes an input module 420 that accepts phrasesinput by a user. It should be recognized that a specific implementationof the input module 420 depends in part upon the type of user interfaceimplemented. Typical components that can be used include text boxes,radio boxes, and check boxes, among others.

The user interface 410 also includes a transmitter module 430 that sendsinformation, including suggestions, to a search server 440. The searchserver 440 performs certain actions relating to suggestions andtransmits information to a receiver module 450 of the user interface410. The receiver module 450 conveys received information to apresentation component 460 that conveys information to the user.

In an exemplary mode of operation of the dynamic search user interface400, the user interface 410 is implemented as a hypertext markuplanguage (“HTML”) document that includes JavaScript, a Java Applet, oranother suitable component. The document and associated component(s) arerendered or executed, as appropriate, within a typical web browser. TheHTML document can include settings or search selections or preferencesthat are selectable through on-screen buttons or the like. Among thetechnologies that may be employed are web services, other scriptinglanguages, other modules to replace Applets, and other types of datastorage and retrieval systems.

A user can position a cursor within a text box associated with a searchand begin typing on a keyboard. The input module 420 will then acceptthe characters typed by the user and send those characters to thetransmitter module. The transmitter module 430, which may be implementedin JavaScript, as an Applet, or other suitable component, transmits thetyped characters as a phrase or phrases to the search server 440.

Based upon the phrase or phrases submitted and other factors such aswhether the phrase or phrases is or are to be treated as a prefix, asuffix, or otherwise, the search server will identify at least onesuggestion. It should be noted that a default category such as “nothingfound” can be implemented as a catch-all or default suggestion. Thesearch server 440 then transmits information including a suggestion tothe receiver module 450. The receiver module 450 then conveys thereceived suggestion to the presentation component 460. The presentationcomponent can cause the user interface 410 to display a list ofsuggestions to the user. Alternatively or additionally, the presentationcomponent can cause a set of preliminary search results based at leastupon one or more suggestions to be displayed to the user. The user canthen select or accept a suggestion or can continue to create a phrase.If the user continues to create a phrase, a new suggestion can then becreated and sent again to the search server 440 for the identificationof new suggestions.

FIG. 5 is system block diagram of a dynamic search client 500 that alsoincludes user feedback functions. The dynamic search client 500 includesa user interface 510. The user interface 510 can be a text-basedinterface, a graphical user interface, a command line interface, or anyother suitable interface, specifically including any of the interfacespreviously discussed in conjunction with other figures. The userinterface 510 specifically can accept data entered by user and canpresent data, such as results of search queries, back to the user in ahuman-readable form. Additionally, the user interface 510 can cooperatewith other components to provide an interactive search environment tothe user.

A query suggestion module 520 can communicate with the user interface510 to obtain portions of a phrase entered by a user. Such portions canbe individual letters that are included in the phrase being built by auser, can be portions of words, or can be groups of words to be includedas search terms for query, among other things as described above withreference to other figures. The query suggestion module 520 can accessinformation from a suggestion data store 530 in order to determine anappropriate manner in which to suggest a query to substitute for a querybeing entered as a phrase by a user at the user interface 510. The querysuggestion module 520 can also access information from a user feedbackmodule 540 in order to adjust a manner in which the query wouldotherwise be completed. The user feedback module 540 can provideinformation from a feedback data store 550 and assist the querysuggestion module 520 in suggesting a partial query for the user in sucha way that is more likely to result in the obtaining of responsiveinformation than could be achieved without the use of such feedbackinformation.

Information in the feedback data store 550 can be compiled from analysisof a user's interaction with the results of search queries over time.For example, if responsive information is presented to the user as aseries of hyperlinks, individual hyperlinks within the series can beranked and a user's interaction with each hyperlinked result, such as byclicking, can be tracked and used to measure quality of the query thatprovided the results. A click by a user on a highly-ranked result can betaken as an indication that the suggested query was highly effective atlocating information that the user deems to be responsive to hisinquiry. Additionally or alternatively, a user's click on a low-rankedresult can be taken as an indication that the suggested query was ofpoor quality and needs to be improved.

Feedback from a user can also be used immediately to improve searchresults, phrase suggestions, or both. For example, the user interface510 can include a component that the user can select to indicate thatnone of the suggestions presented is desired. Such a selection by theuser can be employed to cause the query suggestion engine 520 toaggressively look for spelling corrections, grammatical suggestions, orfor uses of entered phrases in other subject domains. For example, ifthe user enters “Saturn,” a first set of suggestions presented to theuser can have a common theme of astronomy-related results. When the userindicates that such suggestions are not appropriate for his specificquery, the query completion engine 520 can provide new suggestions inthe domain of mythology. Additionally or alternatively, the user canmanipulate a control of the user interface 510, such as a slider, toindicate relative numbers of corrections, as opposed to suggestions, aredesired.

The user feedback module 540 or the feedback data store 550, or both,can be implemented as server on a remote computer. In such an exemplaryimplementation, the user feedback module 540 can take into accountsearches and search queries from a large number of users. Similarly, thequery suggestion module 520 and the query data store 530 can also beimplemented on a remote computer to obtain similar benefits frominformation gathered from a large number of users. By leveraging largeramounts of information from a wide variety of users, query suggestiontasks can be further refined to take into account such things as contextand most likely desired results.

For example, depending upon certain real-life events, probabilities canbe assigned to various search terms in order to attempt to maximize alllikelihood that a user obtains responsive information to his query. Forinstance, a user who enters “sta” at one point in time, such as upon anopening weekend of a popular movie release, can have that querycompleted as “star maps,” but at a second point in time can have thatsame root completed as “collecting stamps.”

One possible mode of operation of the dynamic search client 500 follows.The user interface 510 accepts a portion of a query from a user. As theuser enters each portion of the query, the user interface 510 can sendeach portion to the query suggestion module 520. The query suggestionmodule 520 accesses information from the feedback data store 550 that isprovided by the user feedback module 540 and, using that information,selects an appropriate suggestion from the query data store 530. Thequery suggestion module 520 presents the selected query suggestion tothe user through the user interface 510.

FIG. 6 is a system block diagram of a dynamic search client 600 thatalso includes content association functions. The dynamic search client600 includes a user interface 610. The user interface 610 to be atext-based interface, a graphical user interface, a command lineinterface, or any other suitable interface, specifically including anyof the interfaces previously discussed in conjunction with otherfigures. The user interface 610 specifically can accept data entered bya user and can present data, such as results of search queries, back tothe user in a human-readable form. Additionally, the user interface 610can cooperate with other components to provide an interactive searchenvironment to the user.

A query suggestion module 620 can provide suggestions for queries thathave been entered, at least in part, by a user through the userinterface 610. The user interface 610 can provide a suggested query to asearch server 630. The search server 630 can use the suggested query aspart of a search of information contained in a search data store 640.The search data store 640 can be any suitable data store such as anindex of websites or a database, among others.

The search server 630 can also access information from a contentassociator 650. The content associator 650 can use the suggested querysubmitted from the user interface 610, results of a search of the searchdata store 640, or both, to locate content from an associated contentdata store 660 to associate with results of the search for presentationto user. As with other data stores, the associated content data store660 can be a database, can be a file, can be a group of files, or can beany suitable means of storing information for retrieval in accordancewith the specific implementation. The content associator 650 canassociate content, such as advertising, with results of the searchperformed by the search server 630. The search server 630 can thenprovide information that is responsive to the query along withassociated content to the user interface 610 for presentation to theuser.

A possible manner of operating the dynamic search client 600 follows.The user interface 610 accepts a phrase entered by a user. The phrase issent to the query suggestion module 620 so that the query suggestionmodule 620 can suggest a possible query. The possible query suggestioncan be a simple word suggestion or phrase suggestion, or a more complexsuggestion, such as those types of suggestions previously described inconjunction with other figures. The user interface 610 then sends thesuggested search query to the search server 630. This search server 630uses the suggested query to obtain responsive information from thesearch data store 640.

The content associator 650 accesses the responsive information obtainedby the search server 630 and analyzes that responsive information toform a second query. The second query is used by the content associator650 to obtain content from the associated content data store 660. Inthis specific example, information in the associated content data store660 includes advertising. Content obtained from the associated contentdata store 660 that is responsive to the second query is provided to thesearch server 630. The search server 630 sends both the responsiveinformation and the associated contents to the user interface 610 forpresentation to the user. In this manner, advertising can be targeted toindividuals who are most likely to be responsive to such advertisingbecause the advertising content from the associated content data store660 is specifically associated with information that is responsive to aquery performed by the user.

FIG. 7 is a system block diagram of a dynamic search client system 700that includes structuring functions. The dynamic search client system700, as shown in this specific example, is specifically adapted for dataretrieval tasks that include or support an ability to use structuredqueries, such as queries composed in the Structured Query Language (SQL)or another structured language. Such a client search system can providea relatively informal or natural language interface for a system thatrequires data queries to be input in a highly formal manner that mayrequire highly specialized training to master.

The dynamic search client system 700 includes a user interface 710. Theuser interface 710 can be a text-based interface, a graphical userinterface, a command line interface, or any other suitable interface,specifically including any of the interfaces previously discussed inconjunction with other figures. The user interface 710 specifically canaccept data entered by the user and can present data, such as results ofsearch queries, back to the user in a human-readable form. Additionally,the user interface 710 can cooperate with other components to provide aninteractive search environment to the user.

The user interface 710 can communicate with a query suggestion engine720. Specifically, the user interface 710 can provide a phrase to thequery completion engine 720. The query suggestion engine 720 can, basedupon a variety of factors such as factors or methods previouslydiscussed in conjunction with other figures, suggest a substitute phrasefor the phrase entered at the user interface 710 to be used as a searchquery. In this specific example, the suggested phrase can include agroup of key words or a natural language query in sentence form, amongothers. The query suggestion engine 720 can then send a suggested queryto a structuring engine 730. The structuring engine 730 can use thesuggested query from the query suggestion engine 720 to create astructured query that can be used by a search engine 740. For instance,the natural language query sent by the query suggestion engine 720 canbe transformed into an SQL statement. The SQL statement can be sent bythe structuring engine 730 to the search engine 740. The search engine740 can use the SQL statement to identify and obtain responsiveinformation from a search data store 750. The search engine 740 sendsthe responsive information from the search data store 750 to the userinterface 710 for presentation to the user.

FIG. 8 is a diagram of a user interface 800 that can be employed withvarious disclosed and described components of a dynamic search client.The user interface 800 includes a group of function selection links 810that allow a user to designate a field for a search. Specificallydepicted fields include the World Wide Web, News sites, Images, and theuser's Desktop, which typically includes files on the user's machinewhether that machine is a desktop PC. Laptop computer, or other machine,or whether those files are located on a logical desktop of a GUI or atsome other location in a file system. A Results check box 820 allows theuser to select whether results of partial searches are to be shown.

A text entry box 830 allows a user to enter a phrase. As shown, a phrasehas been entered. Suggestions, along with a number of possible hits orresults for a search on that suggestion, are listed in a drop-down textfield 840. These suggestions can be selected by the user for use as acomplete query by selecting a desired entry with a mouse and thenclicking on the Search button 850 in order to submit the suggestion as aquery for a search.

As the user enters a phrase, results are displayed in a results area860. In this example, the results are based upon a preliminary search,which can be cached, using the topmost suggestion. As a user continuesto type, the list of suggestions can change as the user provides a morecomplete phrase. Therefore, results of a preliminary search can changeas well. The user can submit a suggestion as a query at any time byclicking on the Search button 850. Similarly, the user can terminate thecreation of a suggested query by navigating directly to one of thepreliminary search results displayed in the results area 860.

It should be appreciated that other complex data can be presented to theuser instead of, or in addition to, preliminary search results. Suchpresentations can be in the form of sponsored links to advertisers' websites, online services, multimedia previews, or another appropriateinformation presentation. Additionally, such corrective functions asspell checking and alternative spelling or terms can be presented.

Those of ordinary skill in the art should also recognize that otherinformation may be combined with user-entered phrase to further refinesearch results. For example, all of the user's activities at thecomputer can be monitored or logged. That monitored or loggedinformation can then be used as part of the system to tailor searchresults, to pre-load results based upon the suggestion used as a prefix,or to otherwise optimize search parameters. Also notable is that serverscan coordinate information in a variety of ways. The search serveritself can include a group of individual servers or can simply be acomponent on the user's own machine. Servers can communicate with eachother directly instead of, or in addition to, communicating with theuser interface or other client component. Intermediate systems can alsobe employed to make processing more efficient or for other concerns suchas security. Of course, separate servers can be used for guide andsearch functions.

With reference to FIGS. 9-14, flowcharts in accordance with variousmethods or procedures are presented. While, for purposes of simplicityof explanation, the one or more methodologies shown herein, for example,in the form of a flow chart, are shown and described as a series ofacts, it is to be understood and appreciated that neither theillustrated and described methods and procedures nor any components withwhich such methods or procedures can be used are necessarily limited bythe order of acts, as some acts may occur in a different order and/orconcurrently with other acts from that shown and described herein. Forexample, those skilled in the art will understand and appreciate that amethodology could alternatively be represented as a series ofinterrelated states or events, such as in a state diagram. Moreover, notall illustrated acts may be required to implement a methodology orprocedure.

FIG. 9 is a flow diagram showing processing of a method 900 that can beused. Processing begins at START block 905 and proceeds to process block910 where a user activates a search interface. At process block 915 theuser begins to enter a phrase. The user interface segments the phrase atprocess block 920 and sends a segment to a guide engine at process block925. The guide engine selects suggestions at process block 930. Atprocess block 935, the suggestions are sent to the user.

The user, at process block 940, selects a suggestion from among thesuggestions sent. Upon selecting a suggestion, a complete query isformed from the suggestion and sent to a search server at process block945. The search server then generates a set of search results andtransmits those results back to the user at process block 950.Processing terminates at END block 955.

FIG. 10 is a flow diagram showing processing of a method 1000 that canbe used in accordance with certain disclosed components. Processingbegins at START block 1005 and proceeds to process block 1010 where aphrase is received. At decision block 1015, a determination is madewhether construction of a phrase is already in progress. If no, thephrase is matched with suggestions at process block 1020. If yes,processing continues at process block 1025 where a suggestion subset isobtained to narrow the set of possible suggestions based upon earlierphrase information. Processing proceeds to decision block 1030 where adetermination is made whether it is likely that the phrase being createdby the user is still within an initial subset of completions. Thisdetermination allows for the fact that additional phrase informationprovided by the user can result in a change of the field of a query thatcan be based upon a suggestion. For example, a user who enters “bruin”as a phrase can initially be presented with completions that relate tospecies of bears. However, a more complete phrase such as “bruinshockey” can make it evident that the user desires information not aboutbears but about the sport of ice hockey.

If the determination made at decision block 1030 is yes, processingcontinues to process block 1035 where some number, N, of suggestions isselected. At process block 1040, those suggestions are sent to the user.Processing then terminates at END block 1045. If the determination atdecision block 1030 is no, processing continues to process block 1050where the initial suggestion subset is left. Processing then continuesat process block 1020.

FIG. 11 is a flow diagram depicting acts in a method 1100. Processingbegins at START block 1110 and proceeds to process block 1120 whereevolution of a phrase is monitored. At process block 1130, the phrase issegmented and a search based on that segment is performed at processblock 1140. Results of that search are presented at process block 1150.

At decision block 1160, a determination is made whether the user hasselected a result from among the results presented at process block1150. If no, processing continues to decision block 1170 where adetermination is made whether the phrase entered by the user is stillevolving. If yes, processing continues to process block 1180 where a newsegment is created. Processing then continues to process block 1140where a search based upon the new segment is performed. If thedetermination made at decision block 1160 is yes, processing terminatesat END block 1190. Similarly, if the determination made at decisionblock 1170 is no, processing also terminates at END block 1190.

FIG. 12 is a flow diagram of a general processing flow of a method 1200that can be used with the dynamic search client, such as one or more ofthe dynamic search clients that have been disclosed and described inconjunction with previous figures. Specifically, the general processingflow of the method 1200 can be used in conjunction with a dynamic searchclient that uses structured queries to obtain information for users. Adynamic search client used in such a capacity can provide an easy touse, natural, and intuitive interface to a data storage system that usescomplex query forms and requires a large amount of specialized trainingto use.

Processing of the method 1200 begins at START block 1210 and continuesto process block 1220. At process block 1220, a query suggestion isobtained. The query suggestion can be a query suggested by a querysuggestion engine such as one of the query suggestion engines disclosedand described in conjunction with previous figures. Processing continuesto process block 1230 where the suggested query is structured inaccordance with particular requirements of an environment within whichthe method 1200 is being used. For example, if the processingenvironment includes a relational database, the suggested query can beconverted into an SQL query using a variety of approaches, including theuse of, definitions of, or assumptions about tables to be accessed orvarious aggregation functions to be performed, among others. It shouldbe noted that particulars of structuring a query can and usually willvary greatly depending upon a specific implementation.

At process block 1240, the structured query is sent to a search server.The search server can access some store of data, such as a relationaldatabase, and use the structured query to locate information within thatstore of data that is responsive to the structured query. The responsivedata is obtained and packaged as a set of results at process block 1250.The packaging of the set of results also can vary greatly in formingcontent depending upon a specific implementation. For example, resultscan be formatted as a set of documents that are represented byhyperlinks that can be clicked on by a user to access the specificresults within the result set.

The results set, or least a portion thereof, is presented to a user atprocess block 1260. At decision block 1270, a determination is madewhether the suggested query has been modified from its original form.Such modification can take place because of the operation of the dynamicsearch client that incrementally or continually refines or updates aphrase that is created or entered by a user. In such case, the modifiedsuggested query can be structured and a search based thereon will likelygenerate a different result set.

If the determination made a decision block 1270 is yes, processingreturns to process block 1220 where the newly-modified suggested queryis obtained and thereafter structured at process block 1230. If thedetermination made at decision block 1270 is no, processing terminatesat end block 1280. It should be appreciated that a query can be modifiedin this manner more than once. To conserve processing resources or forother reasons, a limit can be set that provides a maximum number oftimes that a particular query can be modified or otherwise refines anupdate algorithm.

FIG. 13 is a flow diagram of a general processing flow of the method1300 that can be used with the dynamic search client. The method 1300can be used in conjunction with one or more of the dynamic search clientsystems disclosed and described in conjunction with previous figures.Specifically, the method 1300 can be used to provide additional content,such as advertising, and that can be keyed to a specific user query andchange as the user query changes.

Processing of the method 1300 begins at start block 1310 and continuesto process block 1320. At process block 1320, a completed query basedupon a suggestion is obtained. The completed query can be created by adynamic search client that provides suggestions, such as one or more ofthe dynamic search clients that have been disclosed and described inconjunction with previous figures. Processing continues to process block1330 where a search that uses the completed query is performed.Specifics of the search, as will be readily recognized by those ofordinary skill in the art, can vary depending upon a specific searchsystem employed and other implementation aspects.

At process block 1340, results of the search before the process block1330 are obtained. Processing continues at process block 1350 where thesearch results are matched with additional content. A variety ofspecific approaches can be used to match additional content with thesearch results, including using the search query to obtain additionalcontent that is responsive to the query and analyzing the search resultsto create a second search query that can be used to identify and obtainadditional content to be matched, among others. In this manner,additional content such as advertising can be keyed to specificinterests of the user.

Processing continues at process block 1360 where results of the searchbased upon the completed query are presented to the user along with thematched additional content. At decision block 1370, a determination ismade whether the suggestion upon which the completed query originallyobtained has changed. Such a change can be initiated by a user refininga phrase or creating a new phrase, among other things. If thedetermination is yes, processing returns to process block 1320 where anew completed query is obtained. If the determination from decisionblock 1370 is no, processing terminates at end block 1380.

FIG. 14 is a flow diagram of a general processing flow of a method 1400that can be used with one or more of the dynamic search clientsdisclosed and described in conjunction with other figures. Specifically,the method 1400 can be used to obtain user feedback regarding thequality of a completed query for use in improving for future querycompletions. Such user feedback can take a variety of forms,specifically including forms that can be used in a scoring system.

Processing of the method 1400 begins at start block 1410. Processingcontinues to process block 1420 where a completed query that is based atleast in part upon a suggestion is obtained. The complete query can becreated by a dynamic search client that provides suggestions, such asone or more of the dynamic search clients that have been disclose anddescribed in conjunction with previous figures. At process block 1430, asearch is performed using the complete query and a set of search resultsthat are responsive to the completed query is obtained. Those ofordinary skill in the art will readily recognize that specifics of thequery, the search that is performed using that query, and the set ofresults that is obtained will vary based upon, among other things,specific implementation details.

At process block 1440, results from a set of results are presented touser. Processing continues to process block 1450 where user feedback isobtained. In this specific example, it can be assumed that results in aset of results are ranked and that an overall level of quality of theresults in the set is a suitable proxy for a level of quality of thecompleted user query. Ideally, a completed query that is used to performa search will result only in those items of information that are exactlywhat the user desired. However the ideal case is seldom, if ever,realized and steps can be taken to improve completed queries and therebyimprove the quality of search results that are presented to the user.

User feedback can be obtained in a variety of ways. One such way is totrack user interaction with individual items in the result set to anduse associated rankings of those results as part of a scoring system fora query completion that was applied. For example, if a user accesses asearch result that was ranked first in a set of search results, acertain number of points can be added to a score associated with thesearch completion used. Additionally or alternatively, if the useraccesses a result that was ranked lowly, points can be deducted from anassociated score.

Another possible means of obtaining a score to be applied to a querycompletion includes asking a user to indicate whether a particularresult is within a class of results expected by the user. Such anindication can be binary in the sense that a user can simply check a boxor activated radio button or use some other means to indicate whether aresult was responsive to query intended by the user. Additionally oralternatively, a user can be asked to apply a score to the result set aswhole, for example, a rating for the result set ranging from one to ten,or, to apply a score to an individual result within the set from which ascore to be applied to the query completion can be derived. At processblock 1460, a query completion is refined. Details of refinement of aquery completion can and usually will vary according to specificimplementation details. Processing of the method 1400 terminates at ENDblock 1470.

In connection with prediction, learning, or inference-based tasks,various artificial intelligence-based schemes or components can be usedfor carrying out or implementing certain ones of the componentsdisclosed and described herein. For example, inference of a querycompletion can be facilitated by using an automatic classifier systemand process. Additionally, scoring functions that are applied to querycompletions can be improved or otherwise facilitated by using artificialintelligence-based components.

A classifier is a function that maps an input attribute vector, X=(x₁,x₂, x₃, x₄, . . . x_(n)), to a confidence that the input belongs to aclass, that is, f(X)=confidence(class). Such a classification can employa probabilistic and/or statistical-based analysis (for example,factoring into the analysis utilities and costs) to predict or infer anaction that a user desires to be automatically performed. In the case ofsuggestions, a classifier can identify a pattern that indicates aparticular or likely desired suggestion. Upon such identification, theclassifier can trigger a completion task automatically.

A support vector machine (SVM) is an example of a classifier that can beemployed. The SVM operates by finding a hypersurface in the space ofpossible inputs, which hypersurface attempts to split the triggeringcriteria from the non-triggering events. Intuitively, this makes theclassification correct for testing data that is near, but not identicalto, training data. Other directed and undirected model classificationapproaches include, for example, naive Bayes, Bayesian networks,decision trees, and probabilistic classification models providingdifferent patterns of independence can be employed. Classification asused herein also includes statistical regression that is utilized todevelop models of priority.

As will be readily appreciated from the subject specification,classifiers that can be employed includes those classifiers that areexplicitly trained (for example, by a generic training data) as well asimplicitly trained (for example, by observing user behavior, receivingextrinsic information). For example, SVMs are configured by a learningor training phase within a classifier constructor and feature selectionmodule. Thus, the classifier(s) can be used to automatically perform anumber of functions including, but not limited to, scoring suggestionsfor further refinement or improvement actions.

In order to provide additional context for implementing various aspectsof the subject invention, FIGS. 15-16 and the following discussion isintended to provide a brief, general description of a suitable computingenvironment within which various aspects of the subject invention may beimplemented. While the invention has been described above in the generalcontext of computer-executable instructions of a computer program thatruns on a local computer and/or remote computer, those skilled in theart will recognize that the invention also may be implemented incombination with other program modules. Generally, program modulesinclude routines, programs, components, data structures, etc., thatperform particular tasks and/or implement particular abstract datatypes.

Moreover, those skilled in the art will appreciate that the inventivemethods may be practiced with other computer system configurations,including single-processor or multi-processor computer systems,minicomputers, mainframe computers, as well as personal computers,hand-held computing devices, microprocessor-based and/or programmableconsumer electronics, and the like, each of which may operativelycommunicate with one or more associated devices. The illustrated aspectsof the invention may also be practiced in distributed computingenvironments where certain tasks are performed by remote processingdevices that are linked through a communications network. However, some,if not all, aspects of the invention may be practiced on stand-alonecomputers. In a distributed computing environment, program modules maybe located in local and/or remote memory storage devices.

FIG. 15 is a schematic block diagram of a sample-computing environment1500. The system 1500 includes one or more client(s) 1510. The client(s)1510 can be hardware and/or software (e.g., threads, processes,computing devices). The system 1500 also includes one or more server(s)1520. The server(s) 1520 can be hardware and/or software (e.g., threads,processes, computing devices). The servers 1520 can house threads orprocesses to perform transformations by employing the subject invention,for example.

One possible means of communication between a client 1510 and a server1520 can be in the form of a data packet adapted to be transmittedbetween two or more computer processes. The system 1500 includes acommunication framework 1540 that can be employed to facilitatecommunications between the client(s) 1510 and the server(s) 1520. Theclient(s) 1510 are operably connected to one or more client datastore(s) 1550 that can be employed to store information local to theclient(s) 1510. Similarly, the server(s) 1520 are operably connected toone or more server data store(s) 1530 that can be employed to storeinformation local to the servers 1540.

With reference to FIG. 16, an exemplary environment 1600 forimplementing various components includes a computer 1612. The computer1612 includes a processing unit 1614, a system memory 1616, and a systembus 1618. The system bus 1618 couples system components including, butnot limited to, the system memory 1616 to the processing unit 1614. Theprocessing unit 1614 can be any of various available processors. Dualmicroprocessors and other multiprocessor architectures also can beemployed as the processing unit 1614.

The system bus 1618 can be any of several types of bus structure(s)including the memory bus or memory controller, a peripheral bus orexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, Industrial StandardArchitecture (ISA), Micro-Channel Architecture (MCA), Extended ISA(EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Peripheral ComponentInterconnect Express (PCI Express), ExpressCard, Card Bus, UniversalSerial Bus (USB), Advanced Graphics Port (AGP), Personal Computer MemoryCard International Association bus (PCMCIA), Firewire (IEEE 1394),Serial Advanced Technology Attachment (SATA), and Small Computer SystemsInterface (SCSI).

The system memory 1616 includes volatile memory 1620 and nonvolatilememory 1622. The basic input/output system (BIOS), containing the basicroutines to transfer information between elements within the computer1612, such as during start-up, is stored in nonvolatile memory 1622. Byway of illustration, and not limitation, nonvolatile memory 1622 caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable ROM (EEPROM), or flashmemory. Volatile memory 1620 includes random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), anddirect Rambus RAM (DRRAM).

Computer 1612 also includes removable/non-removable,volatile/non-volatile computer storage media. For example, FIG. 16illustrates a disk storage 1624. The disk storage 1624 includes, but isnot limited to, devices like a magnetic disk drive, floppy disk drive,tape drive, Jaz drive, Zip drive, LS-100 drive, flash memory card, ormemory stick. In addition, disk storage 1624 can include storage mediaseparately or in combination with other storage media including, but notlimited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage devices 1624 to the system bus 1618, aremovable or non-removable interface is typically used such as interface1626.

The various types of volatile and non-volatile memory or storageprovided with the computer 1612 can be used to store components ofvarious implementations of the data port signaling system disclosed anddescribed herein. For example, with reference to FIG. 1, the guideengine 130 can be implemented as a software module that can be stored onthe disk storage 1624. At runtime, the guide module 130 can be loadedinto the volatile memory 1620 from where machine-interpretable code ofthe signal module 160 can be accessed by the processing unit 1614 andthereby placed into execution.

It is to be appreciated that FIG. 16 describes software that acts as anintermediary between users and the basic computer resources described inthe suitable operating environment 1600. Such software includes anoperating system 1628. The operating system 1628, which can be stored onthe disk storage 1624, acts to control and allocate resources of thecomputer system 1612. System applications 1630 take advantage of themanagement of resources by operating system 1628 through program modules1632 and program data 1634 stored either in system memory 1616 or ondisk storage 1624. It is to be appreciated that the disclosed componentsand methods can be implemented with various operating systems orcombinations of operating systems.

A user enters commands or information into the computer 1612 throughinput device(s) 1636. The input devices 1636 include, but are notlimited to, a pointing device such as a mouse, trackball, stylus, touchpad, keyboard, microphone, joystick, game pad, satellite dish, scanner,TV tuner card, digital camera, digital video camera, web camera, and thelike. These and other input devices connect to the processing unit 1614through the system bus 1618 via interface port(s) 1638. Interfaceport(s) 1638 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1640 usesome of the same type of ports as input device(s) 1636. Thus, forexample, a USB port may be used to provide input to computer 1612, andto output information from computer 1612 to an output device 1640.

Output adapter 1642 is provided to illustrate that there are some outputdevices 1640 like monitors, speakers, and printers, among other outputdevices 1640, which require special adapters. The output adapters 1642include, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1640and the system bus 1618. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asremote computer(s) 1644.

Computer 1612 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1644. The remote computer(s) 1644 can be a personal computer, a server,a router, a network PC, a workstation, a microprocessor based appliance,a peer device or other common network node and the like, and typicallyincludes many or all of the elements described relative to computer1612. For purposes of brevity, only a memory storage device 1646 isillustrated with remote computer(s) 1644. Remote computer(s) 1644 islogically connected to computer 1612 through a network interface 1648and then physically connected via communication connection 1650. Networkinterface 1648 encompasses wired and/or wireless communication networkssuch as local-area networks (LAN) and wide-area networks (WAN). LANtechnologies include Fiber Distributed Data Interface (FDDI), CopperDistributed Data Interface (CDDI), Ethernet, Token Ring and the like.WAN technologies include, but are not limited to, point-to-point links,circuit switching networks like Integrated Services Digital Networks(ISDN) and variations thereon, packet switching networks, and DigitalSubscriber Lines (DSL).

Communication connection(s) 1650 refers to the hardware/softwareemployed to connect the network interface 1648 to the bus 1618. Whilecommunication connection 1650 is shown for illustrative clarity insidecomputer 1612, it can also be external to computer 1612. Thehardware/software necessary for connection to the network interface 1648includes, for exemplary purposes only, internal and externaltechnologies such as, modems including regular telephone grade modems,cable modems and DSL modems, ISDN adapters, and Ethernet cards.

What has been described above includes illustrative examples of certaincomponents and methods. It is, of course, not possible to describe everyconceivable combination of components or methodologies, but one ofordinary skill in the art will recognize that many further combinationsand permutations are possible. Accordingly, all such alterations,modifications, and variations are intended to fall within the spirit andscope of the appended claims.

In particular and in regard to the various functions performed by theabove described components, devices, circuits, systems and the like, theterms (including a reference to a “means”) used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (for example, a functional equivalent), even though notstructurally equivalent to the disclosed structure, which performs thefunction in the herein illustrated examples. In this regard, it willalso be recognized that the disclosed and described components andmethods can include a system as well as a computer-readable mediumhaving computer-executable instructions for performing the acts and/orevents of the various disclosed and described methods.

In addition, while a particular feature may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.Furthermore, to the extent that the terms “includes,” and “including”and variants thereof are used in either the detailed description or theclaims, these terms are intended to be inclusive in a manner similar tothe term “comprising.”

1. A system for guiding a search for information, comprising: a userinterface that accepts a phrase and receives at least one suggestionbased at least in part on the phrase; and a phrase suggestion enginethat matches the phrase with the at least one suggestion.
 2. The systemof claim 1, wherein the user interface is at least one of a command lineinterface, a text-based interface, a graphical user interface, aweb-based interface, a stylus-based interface, a pen-based data inputsystem, a keypad, a speech recognition system, and a handwritingrecognition system.
 3. The system of claim 2, wherein the phrase is oneof a prefix, a regular expression, a suffix, an infix, a pattern, asubstring, and a string.
 4. The system of claim 2, further comprising asearch engine that provides a result set based at least in part upon aquery created using the suggestion.
 5. The system of claim 4, whereinthe user interface includes a speech processing component that acceptsan audio data input to recognize the phrase.
 6. The system of claim 4,wherein the user interface includes a handwriting processing componentthat accepts handwritten data input to recognize the phrase.
 7. Thesystem of claim 6, further comprising a result display component thatdisplays at least a part of the result set from the search engine. 8.The system of claim 4, wherein the user interface further comprises apresentation component that presents the suggestion to the user.
 9. Amethod of guiding a search for information stored in a machine-readableformat, comprising: creating a suggestion from a phrase entered by auser at a user interface; and creating at least one query based at leastin part upon the suggestion.
 10. The method of claim 9, wherein creatinga suggestion includes referencing a set of suggestions.
 11. The methodof claim 10, wherein referencing a set of suggestions includesreferencing a probability measure.
 12. The method of claim 10, whereinreferencing a set of suggestions includes referencing a ranking ofsuggestions.
 13. The method of claim 10, further comprising searchingfor results that are based at least in part upon a query derived fromthe suggestion.
 14. The method of claim 13, further comprisingpresenting results that are based at least in part upon the query.
 15. Asystem for guiding a search for information stored in a machine-readableformat, comprising: means for creating a suggestion from a phraseentered by a user at a user interface; and means for creating at leastone query based at least in part upon the suggestion.
 16. The system ofclaim 15, wherein the means for creating a suggestion includes means forreferencing a set of suggestions.
 17. The system of claim 16, whereinthe means for referencing a set of suggestions includes means forreferencing a probability measure.
 18. The system of claim 16, whereinthe means for referencing a set of suggestions includes means forreferencing a ranking of suggestions.
 19. The system of claim 16,further comprising means for searching for results that are based atleast in part upon a query derived from the suggestion.
 20. The systemof claim 19, further comprising means for presenting results that arebased at least in part upon the query.